code: def generate_neuropod_torchscript(model: LudwigModel):
      config = model.config
      inference_module = model.to_torchscript()
      with tempfile.TemporaryDirectory() as tmpdir:
          ts_path = os.path.join(tmpdir, "generated.py")
          with open_file(ts_path, "w") as f:
              f.write(
                  INFERENCE_MODULE_TEMPLATE.format(
                      input_signature=_get_input_signature(config),
                      input_dict=_get_input_dict(config),
                      output_dicts=_get_output_dicts(config),
                  )
              )
  
          spec = importlib.util.spec_from_file_location(
              "generated.ts", ts_path
          )
          gen_ts = importlib.util.module_from_spec(spec)
          spec.loader.exec_module(gen_ts)
  
          gen_module = gen_ts.GeneratedInferenceModule(inference_module)
          scripted_module = torch.jit.script(gen_module)
      return scripted_module
  
file_path: ludwig/ludwig/utils/neuropod_utils.py
imports: import importlib.util
  import logging
  import os
  import tempfile
  from typing import Any, Dict, List
  import torch
  from ludwig.api import LudwigModel
  from ludwig.api_annotations import DeveloperAPI
  from ludwig.constants import NAME
  from ludwig.types import ModelConfigDict
  from ludwig.utils.fs_utils import open_file
label_desc: Use image node_id 4 for calling a global function with example usage: generate_neuropod_torchscript(model) and returns: scripted_module